We have evaluated the performance of our method and competing techniques in classification tasks on large datasets on Amazon EC2 clusters. The project is written in PyTorch [1]} and uses the MPICH library for communication between the different nodes. We worked with the CIFAR-10 dataset [2]} using the ResNet-18 [3]} model. We used a cluster of \(K = 15\)  workers and redundancy \(r = 3\) . This results in partitioning each batch into \(f = 455\)  files. We simulated values of \(q=2,4,6\)  during training.
Detailed information about the implementation can be found in Appendix Section REF .
